Mitchell H. Gail, M.D., Ph.D.
NIH Distinguished Investigator
9609 Medical Center Drive
Rockville, MD 20850
Dr. Mitchell Gail has made invaluable contributions to epidemiology and cancer prevention with his expertise in statistical modelling. Most notably, he developed the NCI Breast Cancer Risk Assessment Tool, the first model to estimate a woman's risk of developing invasive breast cancer over the next 5 years and up to age 90 (lifetime risk).
- Developing statistical methods for epidemiologic studies, including intervention trials and genetic epidemiologic studies
- Modeling absolute risk of disease, including breast cancer risk projection
Dr. Gail received an M.D. from Harvard Medical School in 1968 and a Ph.D. in statistics from George Washington University in 1977. He joined NCI in 1969, and served as Chief of the Biostatistics Branch from 1994 to 2008. Dr. Gail is a Fellow and former President of the American Statistical Association, a Fellow of the American Association for the Advancement of Science, an elected member of the American Society for Clinical Investigation, and an elected member of the Institute of Medicine of the National Academy of Sciences. He has received the Spiegelman Gold Medal for Health Statistics, the Snedecor Award for applied statistical research, the Howard Temin Award for AIDS Research, the NIH Director's Award, the PHS Distinguished Service Medal, and the Nathan Mantel Lifetime Achievement Award. He was elected as the Chair-Elect of the Section on Statistics at the American Association for the Advancement of Science (AAAS) and was selected to deliver the prestigious 2013 NIH Robert S. Gordon, Jr. Lecture in Epidemiology. He was named an NIH Distinguished Investigator in 2019.
Li WQ, Ma JL, Zhang L, Brown LM, Li JY, Shen L, Pan KF, Liu WD, Hu Y, Han ZX, Crystal-Mansour S, Pee D, Blot WJ, Fraumeni JF Jr, You WC, Gail MH. Effects of Helicobacter pylori treatment on gastric cancer incidence and mortality in subgroups. J Natl Cancer Inst. 2014;106(7).
Park JH, Anderson WF, Gail MH. Improvements in US Breast Cancer Survival and Proportion Explained by Tumor Size and Estrogen-Receptor Status. J Clin Oncol. 2015;33(26):2870-6.
Park JH, Gail MH, Greene MH, Chatterjee N. Potential usefulness of single nucleotide polymorphisms to identify persons at high cancer risk: an evaluation of seven common cancers. J Clin Oncol. 2012;30(17):2157-62.
Wu J, Pfeiffer RM, Gail MH. Strategies for developing prediction models from genome-wide association studies. Genet Epidemiol. 2013;37(8):768-77.
Related Scientific Focus Areas
Genetics and Genomics
This page was last updated on October 20th, 2020